(Customer Personality Analysis)

by (Mohamed Gamal)

Customer Personality Analysis is a detailed analysis of a company’s ideal customers. It helps a business to better understand its customers and makes it easier for them to modify products according to the specific needs, behaviors and concerns of different types of customers..

Load in your dataset and describe its properties through the questions below. Try and motivate your exploration goals through this section.

What is the structure of your dataset?

This dataset gives 2240 different customers basic information, their product purchasing preferences as well as their reactions to some marketing compaigns Income hase 24 cell missing value

What is/are the main feature(s) of interest in your dataset?

What features in the dataset do you think will help support your investigation into your feature(s) of interest?

Your answer here!

Data Assisment

drop null value in income column

-Need Calc Age From Year of bearth

Get Children Number From Kidhome and Teenhome

get if have children

dt_customer fix data tipe to date

Drop id ,Z_Revenue and Z_CostContact

calc All spent from customer

replace basic and 2n Cycle to ungruate

Get children Number and if have chilfren

Drop id ,Z_Revenue and Z_CostContact

calc All spent from customer

replace basic and 2n Cycle to ungruate

Clustring

Optimal value of K = 4

Univariate Exploration

In this section, investigate distributions of individual variables. If you see unusual points or outliers, take a deeper look to clean things up and prepare yourself to look at relationships between variables.

Make sure that, after every plot or related series of plots, that you include a Markdown cell with comments about what you observed, and what you plan on investigating next.

Discuss the distribution(s) of your variable(s) of interest. Were there any unusual points? Did you need to perform any transformations?

Your answer here!

Of the features you investigated, were there any unusual distributions? Did you perform any operations on the data to tidy, adjust, or change the form of the data? If so, why did you do this?

Your answer here!

Bivariate Exploration

In this section, investigate relationships between pairs of variables in your data. Make sure the variables that you cover here have been introduced in some fashion in the previous section (univariate exploration).

Talk about some of the relationships you observed in this part of the investigation. How did the feature(s) of interest vary with other features in the dataset?

Your answer here!

Did you observe any interesting relationships between the other features (not the main feature(s) of interest)?

Your answer here!

Multivariate Exploration

Create plots of three or more variables to investigate your data even further. Make sure that your investigations are justified, and follow from your work in the previous sections.

Talk about some of the relationships you observed in this part of the investigation. Were there features that strengthened each other in terms of looking at your feature(s) of interest?

Your answer here!

Were there any interesting or surprising interactions between features?

Your answer here!

At the end of your report, make sure that you export the notebook as an html file from the File > Download as... > HTML menu. Make sure you keep track of where the exported file goes, so you can put it in the same folder as this notebook for project submission. Also, make sure you remove all of the quote-formatted guide notes like this one before you finish your report!